{"title":"Searching Web Data using MinHash LSH","authors":"B. Rao, Erkang Zhu","doi":"10.1145/2882903.2914838","DOIUrl":null,"url":null,"abstract":"In this extended abstract, we explore the use of MinHash Locality Sensitive Hashing (MinHash LSH) to address the problem of indexing and searching Web data. We discuss a statistical tuning strategy of MinHash LSH, and experimentally evaluate the accuracy and performance, compared with inverted index. In addition, we describe an on-line demo for the index with real Web data.","PeriodicalId":20483,"journal":{"name":"Proceedings of the 2016 International Conference on Management of Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 International Conference on Management of Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2882903.2914838","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this extended abstract, we explore the use of MinHash Locality Sensitive Hashing (MinHash LSH) to address the problem of indexing and searching Web data. We discuss a statistical tuning strategy of MinHash LSH, and experimentally evaluate the accuracy and performance, compared with inverted index. In addition, we describe an on-line demo for the index with real Web data.
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